# -*- mode: python -*-
# =============================================================================
#  @@-COPYRIGHT-START-@@
#
#  Copyright (c) 2018-2023, Qualcomm Innovation Center, Inc. All rights reserved.
#
#  Redistribution and use in source and binary forms, with or without
#  modification, are permitted provided that the following conditions are met:
#
#  1. Redistributions of source code must retain the above copyright notice,
#     this list of conditions and the following disclaimer.
#
#  2. Redistributions in binary form must reproduce the above copyright notice,
#     this list of conditions and the following disclaimer in the documentation
#     and/or other materials provided with the distribution.
#
#  3. Neither the name of the copyright holder nor the names of its contributors
#     may be used to endorse or promote products derived from this software
#     without specific prior written permission.
#
#  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
#  AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
#  IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
#  ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
#  LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
#  CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
#  SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
#  INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
#  CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
#  ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
#  POSSIBILITY OF SUCH DAMAGE.
#
#  SPDX-License-Identifier: BSD-3-Clause
#
#  @@-COPYRIGHT-END-@@
# =============================================================================

"""Common type definitions that are used across aimet"""

from enum import Enum
from typing import List, Optional, Union
import tensorflow as tf

from aimet_common.defs import GreedySelectionParameters


# Ways to handle getting number of channels from axes. Default is to get it from the last dimension. For depthwise
# conv2d, it will be obtained from the last two dimensions.
class AxisHandling(Enum):
    """
    Enum for axis handling used as input variable to QcQuantizePerChannelOp. This defines how to interpret the
    number of output channels from the weight dimensions.
    """

    LAST_AXIS = 0
    LAST_TWO_AXES = 1


class ModuleCompRatioPair:
    """
    Pair of tf.Operation and a compression-ratio
    :ivar module: Module of type tf.Operation
    :ivar comp_ratio: Compression ratio. Compression ratio is the ratio of cost of compressed model
            to cost of the original model.
    """

    def __init__(self, module: tf.Operation, comp_ratio: float):
        self.module = module
        self.comp_ratio = comp_ratio


class SpatialSvdParameters:
    """Configuration parameters for spatial svd compression"""

    class ManualModeParams:
        """
        Configuration parameters for manual-mode spatial svd compression
        """

        def __init__(self, list_of_module_comp_ratio_pairs: List[ModuleCompRatioPair]):
            """
            :param list_of_module_comp_ratio_pairs: List of (module, comp-ratio) pairs
            """
            self.list_of_module_comp_ratio_pairs = list_of_module_comp_ratio_pairs

    class AutoModeParams:
        """
        Configuration parameters for auto-mode compression
        """

        def __init__(
            self,
            greedy_select_params: GreedySelectionParameters,
            modules_to_ignore: Optional[List[tf.Operation]] = None,
        ):
            """
            :param greedy_select_params: Params for greedy comp-ratio selection algorithm
            :param modules_to_ignore: List of modules to ignore (None indicates nothing to ignore)
            """
            self.greedy_params = greedy_select_params
            self.modules_to_ignore = (
                [] if modules_to_ignore is None else modules_to_ignore
            )

    class Mode(Enum):
        """Mode enumeration"""

        manual = 1
        """ Manual mode """

        auto = 2
        """ Auto mode """

    def __init__(
        self,
        input_op_names: List[str],
        output_op_names: List[str],
        mode: Mode,
        params: Union[ManualModeParams, AutoModeParams],
        multiplicity=1,
    ):
        """
        :param input_op_names: list of input op names to the model
        :param output_op_names: List of output op names of the model
        :param mode: Either auto mode or manual mode
        :param params: Parameters for the mode selected
        :param multiplicity: The multiplicity to which ranks/input channels will get rounded. Default: 1
        """
        self.input_op_names = input_op_names
        self.output_op_names = output_op_names
        self.mode = mode
        self.mode_params = params
        self.multiplicity = multiplicity
